AP STATISTICS
Instructor: Mr. Josh Urich
Room 216
Contact Info:
Phone: 970-686-8100 ext. 3673
Email: [email protected]
Course Description*
AP Statistics uses an activity and discussion-based approach in which students construct their understanding of the
following conceptual themes:
 Exploring Data: Describing patterns and departures from patterns (20-30%)
 Sampling and Experimentation: Planning and conducting a study (10-15%)
 Anticipating Patterns: Exploring random phenomena using probability and simulation (20-30%)
 Statistical Inference: Estimating population parameters and testing hypotheses (30-40%)
The course is conducive to student engagement in activities and discussions investigating statistical concepts, exploring and
analyzing data, assessing models, and performing simulations using appropriate technology such as TI-83+/TI-84 graphing
calculators and Microsoft Excel. Cooperative group problem solving and student writing are learning approaches that are
utilized. The teacher serves as a facilitator/consultant. All aspects of the course including assignments, exams, activities,
and projects are conceptually oriented, and as a result, the teaching will support this focus.
*Note: as per the College Board course description
Expectations
Be in class on time, prepared, and ready to begin when the bell rings. Participate in classroom activities. Be respectful of
others and avoid being a disturbance in class. Try your hardest, always giving your best. Communicate.
Materials
 Textbook
o Yates, D. S., Moore, D. S., & Starnes, D. S. (2008).
The practice of statistics (3rd ed.). New York: W.H. Freeman.
ISBN: 978-0-7167-7309-2
 TI 83/84 Plus Graphing Calculator
 3 ring binder
AP Exam
The AP exam grade is a weighted combination of the score on the multiple-choice section and on the free-response section.
Students who earn AP exam grades of 3 or above are generally considered to be qualified to receive college credit and/or
placement into advanced courses; however, each college or university determines the awarding of credit and placement. It
is your responsibility to check with individual institutions regarding their individual policies. The cost to take the test is
typically $87.00.
The district expects that students will take the culminating exams that are a part of the course of study for any of the
weighted courses.
Grading
A weighted grading scale will be implemented for this course.
Class Work: 15%
Assessments:
Quizzes: 25%
Exams: 50%
Final Exam: 10%
A
B
C
D
F
90% - 100%
80% - 89%
70% - 79%
60% - 69%
59% - below
A
B
C
D
F
5 Quality Points
4 Quality Points
3 Quality Points
1 Quality Points
0 Quality Points
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Assessments
Quizzes will be administered for each section of a chapter and may be given online. Exams will cover an entire
chapter and will be structured similar to the AP Exam. Each test will include both multiple choice and free
response questions to help prepare you for the AP Exam. Additionally, the exams will be cumulative. Class work
or/and practice problems will be assigned daily, but not every assignment will be graded.
Course Outline
Content Objectives/Skills
Producing Data: Designing Samples,
Designing Experiments
 Distinguish between and discuss
observational studies and
experiments.
 Identify and give examples of
different types of sampling
methods
 Identify and give examples of
sources of bias in sample surveys.
 Identify and explain the basic
principles of experimental design.
 Explain what is meant by
completely randomized design.
 Distinguish between the purposes
of randomization and blocking in
an experimental design.
 Use random numbers from a table
or technology to select a random
sample.
Chapter/Timeframe
Chapter 5
 Section 5.1
 Section 5.2
Exploring Data: Displaying Data with
Graphs, Describing Distributions with
Numbers
 Display data distributions including
bar graphs, pie charts, stemplots,
histograms, ogives, time plots, and
boxplots.
 Interpret graphical displays in
terms of shape, center, and spread
of the distribution, as well as gaps
and outliers.
 Describe distributions of data using
mean, median, five-number
summary, standard deviation,
range, and variance.
 Interpret numerical measures in
context.
 Identify outliers in a data set.
 Explore the effects of a linear
transformation of a data set.
Describing Location in a
Distribution: Measures of Relative
Standing and Density Curves, Normal
Distributions
Chapter 1
 Section 1.1
 Section 1.2
Timeframe:
Approximately 6 blocks
Activities
Bottled or Tap
 Student collect data by taste-testing
various samples of water and try to
determine if the samples are from
bottled water or tap water.
Eenie Meanie
 Students learn what is meant by a
simple random sample and recognize
the variability in subjective and
random sampling techniques by
investigating the helper vs. hinderer
study. Additionally, students use
both a graphing calculator and excel
to perform a simulation to aid in the
investigation.
Jelly Blubbers pt. 1
 Students use various sampling
techniques including convenience,
simple, stratified, clustered, and
systematic then compare and contrast
the advantages/disadvantages of
each.
Timeframe:
Approximately 6 blocks
Departing on Time
 The departure times for flights
leaving from O’Hare Airport and
scheduled to arrive in Mexico City
are listed. Students must rank the
five airlines in terms of most likely
to be on time to least likely to be on
time. Statistical procedures are used
and described in a letter to the
Spanish Club who is interested in the
information.
Chapter 2
 Section 2.1
 Section 2.2
McDonald’s Case Analysis
 Students take the side of prosecution
or defense and provide statistical
reasoning (percentiles, z-scores, etc.)
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




Be able to compute measures of
relative standing for individual
values in a distribution including zscores and percentile ranks.
Demonstrate an understanding of a
density curve, including its mean
and median.
Demonstrate an understanding of
the Normal distribution and the 6895-99.7 Rule.
Use tables and technology to find
the proportion of values on an
interval of the Normal distribution.
Use a variety of techniques
including constructing a normal
probability plot to assess the
Normality of a distribution.
Examining Relationships:
Scatterplots and Correlation, LeastSquares Regression, Correlation and
Regression Wisdom
 Construct and interpret a
scatterplot for a set of bivariate
data.
 Compute and interpret the
correlation r between two
variables.
 Demonstrate an understanding of
the basic properties of the
correlation r.
 Explain the meaning of a least
squares regression line.
 Construct and interpret a regression
line given bivariate data.
 Demonstrate understanding of how
to determine the quality of a
regression line as a model for
bivariate data.
Further Exploration of
Relationships: Transforming to
Achieve Linearity, Relationships
between Categorical Variables,
Establishing Causation
 Identify settings in which a
transformation might be necessary
in order to achieve linearity.
 Use transformations involving
powers and logarithms to linearize
curved relationships.
 Explain and describe the parts of a
two-way table.
 Explain what gives the best
evidence for causation.
 Explain the criteria for establishing
causation when experimentation is
not feasible.
Probability: Simulation, Probability
Models, General Probability Rules
Timeframe:
Approximately 5 blocks
to support their stance regarding a
particular case. Students must
communicate their ideas through a 1page closing argument addressing the
jury.
Building Boats
 Students build aluminum foil boats
and fill them until they sink.
Students must collect and record data
and assess the normality of their
data.
Chapter 3
 Section 3.1
 Section 3.2
 Section 3.3
Timeframe:
Approximately 6 blocks
Barbie Bungee Jumping
 Students collect data based on the
number of rubber bands vs. the
bungee distance of Barbie. Students
then complete a scatter plot,
construct a regression line and
equation of the line, interpret the
equation and line in context, and
determine the correlation coefficient.
Students then apply the information
to make predictions about the
number of rubber bands needed for
bungee distances and vice versa.
Timeframe:
Approximately 4 blocks
Shake It, But Don’t Break It
 Linear transformation activity in
which students collect data then
examine various residual plots to
determine the “best” fit for the data.
Students must communicate clearly
why they chose the plot they did.
Chapter 6
 Section 6.1
Lucky Ducks
 Students complete various
Chapter 4
 Section 4.1
 Section 4.2
 Section 4.3
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
Perform simulations using random
number tables and technology (TI83/83+/84)
 Explore sample space using
various methods including lists,
tables, and tree diagrams and use
them to answer probability
questions
 Describe what is meant by the
intersection and union of two event
 Use rules of probability including
additional rules multiplication rules
to solve probability problems
Solve problems involving
conditional probability
Random Variables: Discrete and
Continuous Random Variables, Means
and Variances of Random Variables
 Define what is meant by a random
variable.
 Define a discrete random variable.
 Define a continuous random
variable.
 Explain what is meant by the
probability distribution for a
random variable.
 Explain what is meant by the law
of large numbers.
 Calculate the mean and variance of
a discrete random variable.
 Calculate the mean and variance of
distributions formed by combining
two random variables.
The Binomial and Geometric
Distributions: Binomial
Distributions, Geometric Distributions
 Explain what is meant by a
binomials setting and binomial
distribution.
 Use technology to solve probability
questions in a binomial setting.
 Calculate the mean and variance of
a binomial random variable.
 Solve a binomial probability
problem using a Normal
approximation.
 Explain what is meant by a
geometric setting.
 Calculate the mean and variance of
a geometric random variable.
Sampling Distributions: Sampling
Distributions, Sample Proportions,
Sample Means
 Define a sampling distribution.
 Contrast bias and variability.
 Describe the sampling distribution
of a sample proportion (shape,
center, and spread).


Section 6.2
Section 6.3
Timeframe:
Approximately 7 blocks
Chapter 7
 Section 7.1
 Section 7.2
Timeframe:
Approximately 6 blocks
Chapter 8
 Section 8.1
 Section 8.2
Timeframe:
Approximately 5 blocks
Chapter 9
 Section 9.1
 Section 9.2
 Section 9.3
Timeframe:
Approximately 6 blocks
simulations using a 5-step process in
which they must communicate the
problem, assumptions, method,
simulation, and conclusions.
Casino Lab
 Students explore the rules of
probability in a real-world setting
through the simulation of various
casino games including craps,
blackjack, and roulette.
Plinko
 Students explore the game of Plinko
through simulation using the TI83/84 and answer various questions
including those related to the
binomial distribution.
Jelly Blubbers pt. 2
 Students extend upon random
sampling methods, examine a
sampling distribution, and
communicate the results of the
sampling distribution.
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
Use a Normal approximation to
solve probability problems
involving the sampling distribution
of a sample proportion.
 Describe the sampling distribution
of a sample mean.
 State the central limit theorem.
 Solve probability problems
involving the sampling distribution
of a sample mean.
Estimating with Confidence:
Confidence Intervals, Estimating a
Population Mean, Estimating a
Population Proportion
 Describe statistical inference.
 Describe the basic form of all
confidence intervals.
 Construct and interpret a
confidence interval for a
population mean and for a
population proportion.
 Describe a margin of error and
ways to control the size of the
margin of error.
 Determine the sample size
necessary to construct a confidence
interval for a fixed margin of error.
 Compare and contrast the tdistribution and the Normal
distribution.
 List the conditions that must be
present to construct confidence
intervals for population means and
population proportions.
 Explain what is meant by the
standard error.
 Determine the standard error of x
and p̂ .
Testing a Claim: Significance Tests,
Carrying Out Significance Tests, Use
and Abuse of Tests, Using Inference to
Make Decisions
 Explain the logic of significance
testing.
 List and explain the differences
between a null hypothesis and an
alternative hypothesis.
 Discuss the meaning of statistical
significance.
 Use the Inference Toolbox to
conduct a large sample test for a
population mean.
 Compare two-sided significance
tests and confidence intervals when
doing inference.
 Differentiate between statistical
and practical “significance.”
 Explain and distinguish between
Chapter 10
 Section 10.1
 Section 10.2
 Section 10.3
Paper Airplanes pt. 1
 Students use confidence intervals to
compare flight distances of different
paper airplane models.
Timeframe:
Approximately 6 blocks
Chapter 11
 Section 11.1
 Section 11.2
 Section 11.3
 Section 11.4
TBA
Timeframe:
Approximately 7 blocks
5
Type I and Type II errors in
hypothesis testing.
 Define and discuss the power of a
test.
Significance Tests in Practice: Tests
about a Population Mean, Tests about
a Population Proportion
 Conduct one-sample and paired
data t-tests.
 Explain the difference between the
one-sample confidence interval for
a population proportion and the
one-sample significance test for a
population proportion.
 Conduct a significance test for a
population proportion.
Comparing Two Population
Parameters: Comparing Two Means,
Comparing Two Proportions
 Identify the conditions that need to
be satisfied in order to do inference
for comparing two population
means.
 Construct a confidence interval for
the difference between two
population means.
 Perform a significance test for the
difference between two population
means.
 Identify the conditions that need to
be satisfied in order to do inference
for comparing two population
proportions.
 Construct a confidence interval for
the difference between two
population proportions.
 Perform a significance test for the
difference between two population
proportions.
Inference for Distribution of
Categorical Variables: Chi-Square
Procedures: Test for Goodness of Fit,
Inference for Two-Way Tables
 Explain what is meant by a chisquare goodness of fit test.
 Conduct a chi-square goodness of
fit test.
 Given a two-way table, compute
conditional distributions.
 Conduct a chi-square test for
homogeneity of populations.
 Conduct a chi-square test for
association/independence.
 Use technology to conduct a chisquare significance test.
Inference for Regression
 Identify the conditions necessary to
Chapter 12
 Section 12.1
 Section 12.2
TBA
Timeframe:
Approximately 4 blocks
Chapter 13
 Section 13.1
 Section 13.2
Timeframe:
Approximately 4 blocks
Chapter 14
 Section 14.1
 Section 14.2
Timeframe:
Approximately 4 blocks
Chapter 15
Double Stuf Oreos
 Student collect data to determine
whether or not double stuffed oreos
are really double stuffed.
Paper Airplanes pt. 2
 Students use significance tests to
compare flight distances of different
paper airplane models.
Plain and Peanut
 Students perform a Chi-Square
analysis for both plain and peanut M
& Ms to verify or refute the
company’s claim. Students must
provide a written conclusion of their
results.
Short or Tall
 Students collect a sample of data
Timeframe:
6
do inference for regression.
Given a set of data, check that the
conditions for doing inference for
regression are present.
 Explain what is meant by the
standard error about the leastsquares line.
 Compute a confidence interval for
the slope of the regression line.
 Conduct a test of the hypothesis
that the slope of the regression line
is zero (no correlation) in the
population.
Review for Exam
 2002/2007 Released Multiple
Choice
 Released Free Response items
 Cumulative Final Exam
After Exam
 Group Research
Projects/Presentations
Approximately 2 blocks

regarding height and shoe size then
determine if the slope is significant
using a hypothesis test. Students
must communicate their conclusion
in a written format.
Timeframe:
Approximately 3 blocks
Time Permitting
Research Project
 Students must demonstrate and
communicate various aspects of a
statistical study.
 Students must provide a written
report as well as a brief oral
presentation of their findings.
References
Primary Text:
Yates, D. S., Moore, D. S., & Starnes, D. S. (2008). The practice of statistics (3rd ed.). New York: W.H. Freeman.
Other resourses:
Fathom statistical software
Meaning from Data: Statistics made clear. (2006). Chantilly, VA: The Teaching Company.
Millard, R., & Turner, J. (2004). Activities and projects for high school statistics courses. New York: W.H. Freeman.
Peck, R., Olsen, C., & Devore, J. (2008). Introduction to statistics and data analysis (3rd ed.). California: Thomas
Brooks/Cole.
Powers, R.A. (2010). Applied probability and statistics: Course handbook. Colorado: The Mathematics Teacher Leadership
Center.
Rossman A., Chance B., & Von Oehsen J. (2008). Workshop statistics: Discovery with data and the graphing calculator
(3rd ed.). New Jersey: John Wiley and Sons, Inc.
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